Chen Danyan, Jiang Jiehui, Lu Jiaying, Wu Ping, Zhang Huiwei, Zuo Chuantao, Shi Kuangyu
Shanghai Institute for Advanced Communication and Data Science, Shanghai University, Shanghai, China.
Key Laboratory of Specialty Fiber Optics and Optical Access Networks, Joint International Research Laboratory of Specialty Fiber Optics and Advanced Communication, Shanghai University, Shanghai, China.
Front Neurol. 2019 Apr 12;10:369. doi: 10.3389/fneur.2019.00369. eCollection 2019.
Facilitating accurate diagnosis and ensuring appropriate treatment of dementia subtypes, including Alzheimer's disease (AD), Parkinson's disease dementia (PDD), and Lewy body dementia (DLB), is clinically important. However, the differences in glucose metabolic distribution among these three dementia subtypes are minor, which can result in difficulties in diagnosis by visual assessment or traditional quantification methods. Here, we explored this issue using novel approaches, including brain network and abnormal hemispheric asymmetry analyses. We generated 18F-labeled fluorodeoxyglucose (18F-FDG) positron emission tomography (PET) images from patients with AD, PDD, and DLB, and healthy control (HC) subjects ( = 22, 18, 22, and 22, respectively) from Huashan hospital, Shanghai, China. Brain network properties were measured and between-group differences evaluated using graph theory. We also calculated and explored asymmetry indices for the cerebral hemispheres in the four groups, to explore whether differences between the two hemispheres were characteristic of each group. Our study revealed significant differences in the network properties of the HC and AD groups (small-world coefficient, 1.36 vs. 1.28; clustering coefficient, 1.48 vs. 1.59; characteristic path length, 1.57 vs. 1.64). In addition, differing hub regions were identified in the different dementias. We also identified rightward asymmetry in the hemispheric brain networks of patients with AD and DLB, and leftward asymmetry in the hemispheric brain networks of patients with PDD, which were attributable to aberrant topological properties in the corresponding hemispheres.
促进对痴呆症亚型(包括阿尔茨海默病(AD)、帕金森病痴呆(PDD)和路易体痴呆(DLB))的准确诊断并确保适当治疗在临床上具有重要意义。然而,这三种痴呆症亚型之间葡萄糖代谢分布的差异较小,这可能导致通过视觉评估或传统定量方法进行诊断时出现困难。在此,我们使用包括脑网络和异常半球不对称分析在内的新方法来探讨这个问题。我们从中国上海华山医院的AD、PDD和DLB患者以及健康对照(HC)受试者(分别为22例、18例、22例和22例)中生成了18F标记的氟脱氧葡萄糖(18F-FDG)正电子发射断层扫描(PET)图像。使用图论测量脑网络属性并评估组间差异。我们还计算并探索了四组中大脑半球的不对称指数,以探究两个半球之间的差异是否是每组的特征。我们的研究揭示了HC组和AD组在网络属性上的显著差异(小世界系数,1.36对1.28;聚类系数,1.48对1.59;特征路径长度,1.57对1.64)。此外,在不同的痴呆症中识别出了不同的枢纽区域。我们还发现AD和DLB患者的半球脑网络存在向右不对称,而PDD患者的半球脑网络存在向左不对称,这归因于相应半球中异常的拓扑属性。